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Record W2119939340 · doi:10.2514/6.2012-2678

Numerical Validation of CHT3D/CFX in Anti-/de-Icing Piccolo System

2012· article· en· W2119939340 on OpenAlexaff
Ridha Hannat, François Morency

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsIcingSolverHeat exchangerJet (fluid)Flow (mathematics)TurbulenceThermalMechanicsMaterials scienceMechanical engineeringAerospace engineeringEngineeringComputer sciencePhysicsMeteorology

Abstract

fetched live from OpenAlex

Anti-/de-icing CHT method based on ANSYS-CFX flow solver and FENSAP-ICE software is presented. The ANSYS-CFX flow solver is used as the flow solver module with the , SST turbulence model. DROP3D is used as the droplet impingement module. ICE3D is used as the ice accretion and water film runback module. CHT3D/CFX is used for the thermal coupling of all modules. Before solving for the temperature distribution in a 3D anti-icing system geometry based on a piccolo tube with three jet rows, a test case consisting of a two stream parallel gas to gas micro heat exchangers is used to validate the CHT3D/CFX procedure. For the anti-icing system in wet air mode temperature results at corresponding experimental locations are presented and compared to results from literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.215
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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